The present invention relates to frequency burst detection in wireless communication systems. More specifically, the present invention relates to the detection of the FCH burst in GSM/GPRS systems.
Wireless communication systems such as GSM use a combination of FDMA (Frequency Division Multiple Access) and TDMA (Time Division Multiple Access) to provide access to multiple users. In FDMA/TDMA-based systems, frequency and timing synchronization between the receiver and transmitter is required before they start communicating data. The GSM standard provides a frequency correction burst (FCH burst) for frequency synchronization, and a synchronization burst (SCH burst) for timing synchronization in the Broadcast Control Channel (BCCH) carrier. FCH burst is required to achieve frequency synchronization. However, the accuracy of the detection of the frequency burst depends on timing synchronization. On the other hand, reliable timing synchronization cannot be achieved unless frequency synchronization is achieved with an accuracy of at least 400 to 500 Hz. So there is a need to identify the time of the occurrence of the FCH burst without using timing synchronization.
The FCH burst is in the form of 148 samples comprising successive “zero” signals. The zero signals are transmitted by using Gaussian minimum phase shift keying (GMSK). Therefore, the baseband FCH burst manifests itself as a complex sine wave of frequency Rb/4, where Rb is the bit rate of the transmission. This FCH burst is designed to produce a substantially constant frequency shift in the carrier frequency, which may then be used for frequency correction by the GSM receiver receiving the FCH Burst. The GSM receivers detect the FCH burst in the acquisition phase and use its frequency to synchronize their local oscillators. The FCH burst boundary is also detected to synchronize the time slot boundaries with those of the base station.
However, the baseband FCH burst experiences a frequency offset due to limitations in the accuracy of local oscillators, and multipath effects and noise in the transmission channel. Therefore, FCH detection methods must account for the above-mentioned frequency offset, to successfully detect the FCH burst.
Various methods for detecting the FCH burst in the received signal are known in the art. Conventional FCH detection methods use a bandpass filter of constant bandwidth, centered at the expected frequency of the FCH burst (Rb/4). When the FCH burst is passed through a bandpass filter centered at Rb/4, the input and output powers of the bandpass filter are expected to be almost the same. However, for a data burst the output power of the bandpass filter is much lower than the input power. Therefore, the comparison of the input and output powers is used to detect the occurrence of the FCH burst. A method using a constant bandwidth bandpass filter is disclosed in U.S. patent application No. 20030189978A1, titled “Phase Difference Based Frequency Correction Channel Detector for Wireless Communication System”, to Lin et al. In accordance with the method disclosed in this patent, the received signal is provided to a phase differentiator. The output of the phase differentiator is then passed through a low pass filter to limit the noise and obtain an un-notched signal. Thereafter, the un-notched signal is passed through a notch filter. The ratio of the powers of un-notched and notched signals is then calculated. When the ratio attains a value below a threshold and continues to be the same for a predetermined time, an occurrence of the FCH burst is declared.
Another approach for detecting the FCH burst uses the correlation between the received signal and a reference signal. The reference signal is chosen considering the expected frequency of the FCH burst. A correlation-based FCH detection method is provided in U.S. Pat. No. 6,122,327, titled “Radio Receiver”, assigned to Sony Corporation, Tokyo, Japan. The method, in accordance with above patent, involves the sampling of the baseband received signal with an analog-to-digital converter circuit, and obtaining a correlation value of the sampled signal with a predetermined reference signal. The FCH burst is detected depending on the obtained correlation value.
The above-mentioned FCH detection methods exploit the narrow-band nature of the FCH burst. The methods based on a constant bandwidth filters chose the center frequency of the filter based on the expected frequency of the FCH burst. The correlation-based methods also use a reference signal depending on the expected frequency of the FCH burst. Therefore, the performance of these methods depends on the expected frequency of the FCH burst. In the presence of large frequency offsets, such methods fail to detect the FCH burst accurately, since the frequency of the received FCH burst differs substantially from the expected frequency.
The accuracy of methods based on a constant bandwidth filters also depends on the choice of the bandwidth of the filter. Choosing a large bandwidth allows the detection of the FCH burst, even in the presence of a relatively large frequency offset. However, large bandwidth filters are prone to false detections. On the other hand, choosing a smaller bandwidth reduces the probability of false detections, but is unsuitable for detecting the FCH burst in the presence of large frequency offsets, since it results in misses of some occurrences of the FCH burst.
A variation of the method based on constant bandwidth filter uses a bank of bandpass filters. In such methods, the filters are chosen with different central frequencies. These central frequencies are chosen so that they cover a large range of frequency offsets around the expected frequency of the FCH burst (Rb/4). The detection is performed by comparing the input and output powers of all the filters. This variation is more effective in reducing the misses as well as false detections. However, this improved performance is achieved at the cost of computational complexity. The number of filters required for the successful detection of the FCH burst increases with the frequency offset. Therefore, the method becomes computationally inefficient for large frequency offsets.
Another approach for detecting the FCH burst uses an adaptive bandpass filter. Methods based on adaptive filters involve the adapting of the filter parameters depending on the frequency of the received signal. One such method is disclosed in European Patent No. 0717512A2, titled “Coarse Frequency Burst Detector for a Wireless Communications Systems, Such as for Use with GSM”, and assigned to AT&T Corp. This method involves obtaining the baseband signal from the received signal and derotating the baseband signal. The derotated signal is then filtered through a moving average (MA) filter with adaptive averaging window size. Thereafter, the magnitude of the output of the MA filter in used to tentatively identify the filtered burst as the FCH burst. The frequency of the tentatively identified burst is then used for the frequency compensation of the original baseband signal. The frequency compensated signal is then filtered again with a MA filter with a window size, which is larger than the one used for the previous filtering. The output of the MA filter is then used to confirm the tentatively detected FCH burst. Therefore, the method adapts a combination of frequency compensation and adaptive averaging window-size to accurately detect the FCH burst. The method takes a two-step approach in which the window-size adaptation and frequency compensation has to be performed for all tentatively detected bursts. This makes the method computationally inefficient.
Another method, using an adaptive filter, is proposed in U.S. Pat. No. 5,241,688, titled “Frequency and Time Slot Synchronization Using Adaptive Filtering”, and assigned to Motorola, Inc. Schaumburg, Ill. The method, in accordance with the above patent, involves the filtering of the received signal with an adaptive band-pass filter and buffering the received signal in a memory. The energies of the input signal and the filtered signal are estimated and the gain of the filter is adapted, based on the difference between the energies. Further, the pole of the filter is adapted so that the pass-band of the filter encompasses the received signal. The minimum value of the adapted gain signifies a narrow-band signal and is used to detect the FCH burst in the received signal. Since the method calculates the filter parameters to be adapted at each sample, a substantial amount of computation is required for each sample of data. Additionally, the filter used is an infinite impulse response (IIR) filter. Since the pole of the filter is adapted to the frequency of the received signal, a control logic is required to avoid the instability of the filter. This control logic further adds to the computational complexity of this method.
The above-mentioned FCH burst detection methods using non-adaptive filters suffer from either misses or false detections. Further, the performance of these methods is sensitive to the frequency offset present in the received signal. The adaptive filter based methods providing accurate FCH burst detection with fewer false detections, are computationally complex. Therefore, there exists a need for a computationally efficient method, which can detect the FCH burst with fewer misses or false detections. Further, there exists a need for a FCH detection method that is insensitive to the magnitude of frequency offset in the received signal.